No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by strands-agents · MCP Server · ★ 852
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is samples safe to install? View the security audit →
Strands Agents Samples A model-driven approach to building AI agents in just a few lines of code. Documentation ◆ Samples ◆ Python SDK ◆ <a href="https://github.com/strands-
| Stars | 852 |
| Forks | 442 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 64.6128447578063/100 |
| Open Issues | 46 |
| Last Updated | 2026-09-21 |
| Created | 2025-05-14 |
| Platforms | mcp, python |
| Est. Tokens | ~15k |
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samples is Agent samples built using the Strands Agents SDK.. It is categorized as a MCP Server with 852 GitHub stars.
samples is primarily written in Python. It covers topics such as agentic, agentic-ai, agents.
You can find installation instructions and usage details in the samples GitHub repository at github.com/strands-agents/samples. The project has 852 stars and 442 forks, indicating an active community.
samples is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to samples on Agent Skills Hub include sre, argo, oreilly-ai-agents. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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